Defining the importance of landscape metrics for large branchiopod biodiversity and conservation: the case of the Iberian Peninsula and Balearic Islands

The deficiency in the distributional data of invertebrate taxa is one of the major impediments acting on the bias towards the low awareness of its conservation status. The present study sets a basic framework to understand the large branchiopods distribution in the Iberian Peninsula and Balearic Islands. Since the extensive surveys performed in the late 1980s, no more studies existed updating the information for the whole studied area. The present study fills the gap, gathering together all available information on large branchiopods distribution since 1995, and analysing the effect of human population density and several landscape characteristics on their distribution, taking into consideration different spatial scales (100 m, 1 km and 10 km). In overall, 28 large branchiopod taxa (17 anostracans, 7 notostracans and 4 spinicaudatans) are known to occur in the area. Approximately 30% of the sites hosted multiple species, with a maximum of 6 species. Significant positive co-occurring species pairs were found clustered together, forming 4 different associations of large branchiopod species. In general, species clustered in the same group showed similar responses to analysed landscape characteristics, usually showing a better fit at higher spatial scales.     

Copepods and branchiopods of temporary ponds in the Doñana Natural Area (SW Spain): a four-decade record (1964–2007)

The Doñana Natural Area includes a large array of wetlands with the highest degree of environmental protection in Spain, and so it has long attracted many studies. We present a cumulative list of zooplankton taxa (Copepods and Branchiopods) based on a collection of 18 publications (1964–2007) and 4 unpublished studies. Seventy-eight taxa have been recorded in a set of 55 ponds, and 72 taxa at 38 sites spread over the Doñana marshland. In total, 96 taxa have been recorded, including 50% of all branchiopod species reported for the whole Iberian Peninsula. Taxa composition was significantly segregated between ponds and marshland during floods (ANOSIM test, R = 0.929, P < 0.01), but this segregation disappeared at a larger spatio-temporal scale when a non-metric MDS ordination produced a gradient from ponds to marshland (ANOSIM test, R = 0.272, P < 0.01). The lack of segregation between ponds and marshland sites, and among ponds with different hydroperiods, was not due to a large number of cosmopolitan species, but to a random distribution of a large number of low-occurrence species (67% of total taxa occurred with a frequency <15%). Long-hydroperiod ponds occupy a key position among the Doñana wetlands in terms of biodiversity as these ponds accumulated a high crustacean richness over time. They also supported a significantly higher cumulative number of cladoceran and harpacticoid taxa, while short-hydroperiod ponds accumulated the lowest number of diaptomid taxa. Our data indicate the need for recording biodiversity in the long term as richness on a short-temporal scale is not a good indicator of the number of crustacean species that would be encountered with a longer sampling period in Mediterranean temporary wetlands.     

Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug–drug complex networks

One limitation of almost all antiviral Quantitative Structure–Activity Relationships (QSAR) models is that they predict the biological activity of drugs against only one species of virus. Consequently, the development of multi-tasking QSAR models (mt-QSAR) to predict drugs activity against different species of virus is of the major vitally important. These mt-QSARs offer also a good opportunity to construct drug–drug Complex Networks (CNs) that can be used to explore large and complex drug-viral species databases. It is known that in very large CNs we can use the Giant Component (GC) as a representative sub-set of nodes (drugs) and but the drug–drug similarity function selected may strongly determines the final network obtained. In the three previous works of the present series we reported mt-QSAR models to predict the antimicrobial activity against different fungi [Gonzalez-Diaz, H.; Prado-Prado, F. J.; Santana, L.; Uriarte, E. Bioorg. Med. Chem. 2006, 14, 5973], bacteria [Prado-Prado, F. J.; Gonzalez-Diaz, H.; Santana, L.; Uriarte E. Bioorg. Med. Chem. 2007, 15, 897] or parasite species [Prado-Prado, F.J.; González-Díaz, H.; Martinez de la Vega, O.; Ubeira, F.M.; Chou K.C. Bioorg. Med. Chem. 2008, 16, 5871]. However, including these works, we do not found any report of mt-QSAR models for antivirals drug, or a comparative study of the different GC extracted from drug–drug CNs based on different similarity functions. In this work, we used Linear Discriminant Analysis (LDA) to fit a mt-QSAR model that classify 600 drugs as active or non-active against the 41 different tested species of virus. The model correctly classifies 143 of 169 active compounds (specificity = 84.62%) and 119 of 139 non-active compounds (sensitivity = 85.61%) and presents overall training accuracy of 85.1% (262 of 308 cases). Validation of the model was carried out by means of external predicting series, classifying the model 466 of 514, 90.7% of compounds. In order to illustrate the performance of the model in practice, we develop a virtual screening recognizing the model as active 92.7%, 102 of 110 antivirus compounds. These compounds were never use in training or predicting series. Next, we obtained and compared the topology of the CNs and their respective GCs based on Euclidean, Manhattan, Chebychey, Pearson and other similarity measures. The GC of the Manhattan network showed the more interesting features for drug–drug similarity search. We also give the procedure for the construction of Back-Projection Maps for the contribution of each drug sub-structure to the antiviral activity against different species.     

Characterization of the TRBP domain required for Dicer interaction and function in RNA interference

Background  

Dicer, Ago2 and TRBP are the minimum components of the human RNA-induced silencing complex (RISC). While Dicer and Ago2 are RNases, TRBP is the double-stranded RNA binding protein (dsRBP) that loads small interfering RNA into the RISC. TRBP binds directly to Dicer through its C-terminal domain.     

The cellular prion protein and its role in Alzheimer disease

The cellular prion protein (PrP^C) is a membrane-bound glycoprotein especially abundant in the central nervous system (CNS). The scrapie prion protein (PrP^Sc, also termed prions) is responsible of transmissible spongiform encephalopathies (TSE), a group of neurodegenerative diseases which affect humans and other mammal species, although the presence of PrP^C is needed for the establishment and further evolution of prions.The present work compares the expression and localization of PrP^C between healthy human brains and those suffering from Alzheimer disease (AD).In both situations we have observed a rostrocaudal decrease in the amount of PrP^C within the CNS, both by immunoblotting and immunohistochemistry techniques. PrP^C is higher expressed in our control brains than in AD cases. There was a neuronal loss and astogliosis in our AD cases. There was a tendency of a lesser expression of PrP^C in AD cases than in healthy ones. And in AD cases, the intensity of the expression of the unglycosylated band is higher than the di- and monoglycosylated bands.With regards to amyloid plaques, those present in AD cases were positively labeled for PrP^C, a result which is further supported by the presence of PrP^C in the amyloid plaques of a transgenic line of mice mimicking AD.The work was done according to Helsinki Declaration of 1975, and approved by the Ethics Committee of the Faculty of Medicine of the University of Navarre.Key words: cellular prion protein, Alzheimer disease, transgenic mice     

Spatio-temporal nested patterns in macroinvertebrate assemblages across a pond network with a wide hydroperiod range

Nestedness has been widely used to measure the structure of biological communities and occurs when species-poor sites contain subsets of species-rich ones. Here, we examine nested patterns across the macroinvertebrate assemblages of 91 ponds in Doñana National Park, Spain, and explore temporal variation of nestedness and species richness in 19 temporary ponds over 2 years with differing rainfall. Macroinvertebrate assemblages were significantly nested; both pond spatial arrangement and environmental variation being important in driving nested patterns. Despite the nested structure observed, a number of taxa and ponds deviate from this pattern (termed idiosyncratic), by occurring more frequently than expected in species-poor sites, or having assemblages dominated by species largely absent from species-rich sites. Aquatic adults of winged insects, capable of dispersal, were more highly nested than non-dispersing taxa and life-history stages. Idiosyncratic taxa were found in ponds spanning a wide range of hydroperiods, although nestedness was higher in more permanent waterbodies. Monthly sampling demonstrated a gradual increase of species richness and nestedness from pond filling to April–May, when the most temporary ponds started to dry. Although the degree of nestedness of individual pond assemblages varied from month to month, the overall degree of nestedness in the two study years was practically identical despite marked differences in hydroperiod. Our results suggest that differential colonization and environmental variation are key processes driving the nested structure of Doñana ponds, that macroinvertebrate assemblages change in a predictable manner each year in response to cycles of pond wetting and drying, and that connectivity and environmental variability maintain biodiversity in pond networks.     

Computational methods for the prediction of protein interactions

Establishing protein interaction networks is crucial for understanding cellular operations. Detailed knowledge of the 'interactome', the full network of protein-protein interactions, in model cellular systems should provide new insights into the structure and properties of these systems. Parallel to the first massive application of experimental techniques to the determination of protein interaction networks and protein complexes, the first computational methods, based on sequence and genomic information, have emerged.